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workflows, and data engineering for mobility platforms • AI/ML for transportation prediction, system optimization, and environmental/health impact modeling • Deployment of decision-support tools for public
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in New York, across the nation, and around the world. Position Function The CNCPS was modified to be able to predict nitrogen (N) and phosphorous (P) excretion, and this was published by Fox et al
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to predict nitrogen (N) and phosphorous (P) excretion, and this was published by Fox et al. (2004). Further, those predictions were refined and improved and partition N and P excretion between urine and feces
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for transportation prediction, system optimization, and environmental/health impact modeling Deployment of decision-support tools for public-sector clients (municipalities, MPOs, DOTs) Urban mobility, equity
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their impact on gene expression. Contribute to large-scale modeling of engineered traits to predict performance and optimize design. Required Qualifications: PhD in the field of genomics, evolution, population
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variants as functional and assess their impact on gene expression. Contribute to large-scale modeling of engineered traits to predict performance and optimize design. Required Qualifications: PhD in
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Systems Engineering (Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support Platforms) as part of the CTECH Postdoctoral Fellows program. This
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research encompasses (but is not limited to) identifying effective tutoring practices, running experiments on AI tutors in simulated and real-world environments, fine-tuning AI models to classify qualitative
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knowledge representation • Agent-based and simulation modeling • AI/ML, foundation models, causal inference, and predictive analytics • Human factors, behavior science, and patient-centered design • Advanced
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real-world environments, fine-tuning AI models to classify qualitative data, and building generative AI pipelines to process multimodal data for downstream analysis. Applicants with experience in some